The new age of information technologies demands systems aimed to be every time more dynamic and composed by heterogeneous entities. These entities must be able to enter and exit the system, interact with each other, and adapt themselves due to environmental requirements. In the last decades, multiagent systems have contribute to model, design, and implement autonomous systems with interaction and communication capabilities. These systems are usually designed through agent societies, which facilitate the interaction, organization, and cooperation of heterogeneous agents in order to achieve different goals. In order to this paradigm be suitable for the development of the next-generation systems, features such as dynamicity and adaptability must be provided for modeling, managing, and executing agent societies.

In more detail, reorganization in agent societies provides a paradigm for designing open, dynamic, and adaptive applications. This process requires determining the consequences of applying changes not only in terms of the benefits provided, but also measuring the adaptation costs as well as the impact that these changes have on all the components of the system. The few existing approaches for reorganization mainly focus this process as responses to the society when changes occur, or as a mechanism for maximizing the utility of the system. However, it is not possible to define complex deliberation processes that obtain the best organizational configuration at each moment, based on an accurate measurement of the benefits obtained by reorganization and the costs associated to this process. 

With this goal in mind, this thesis explores the area of reorganization in agent societies and focuses specifically on a novel approach for reorganization. This approach provides a decision-making support that considers reorganization in multiple organizational dimensions and is aimed at obtaining the adaptation with the highest potential for improvement in utility based on the costs of reorganization. By considering different requirements of the final configuration that is to be achieved, our approach accurately predicts the impact of the reorganization in terms of two aspects: the costs associated to carry out the reorganization process, and the benefits or costs that this process causes not only to the agents involved in the change but also to the whole system. Moreover, since several changes on different dimensions can be considered, the range of adaptation solutions is increased.